Abstract: Driven by rapid development of computing and mathematical techniques,
computer simulations have emerged as a critical tool in engineering design.
To cut down simulation times, surrogate models are widely used for building
approximations of time-consuming computer simulation codes in a large array
of engineering design problems. The prevailing framework for building surrogate
models deals almost exclusively with quantitative design factors only.
However, many engineering design problems involve both quantitative and
qualitative design factors. In this talk, we will introduce an easy-to-implement
surrogate modeling method for computer experiments with both quantitative
and qualitative input variables. The method can also be adopted as an integrated
meta-modeling tool for computer simulations with multivariate output to
improve surrogate model prediction accuracy. Novel experimental design and
model selection procedures for such surrogate modeling scheme will also be
discussed. Case studies have been conducted to demonstrate the effectiveness
of our methods. Some other projects in quality engineering will also be
briefly discussed in the end of this talk.